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. 2024 Apr 16;19(4):e0301847.
doi: 10.1371/journal.pone.0301847. eCollection 2024.

Effectiveness of the online-eLearning program KeepCoool at improving the vaccine cold chain in general practices

Anika Thielmann  1 , Marie-Therese Schmitz  2 , Thomas Welchowski  1   2 , Birgitta Weltermann  1
Affiliations

Effectiveness of the online-eLearning program KeepCoool at improving the vaccine cold chain in general practices

Anika Thielmann et al. PLoS One. .

Abstract

Background: Protecting vaccines from freeze damage is a poorly addressed problem. We describe the effectiveness of the eLearning KeepCoool on cold chain maintenance in general practices.

Methods: For this intervention study, temperatures of vaccine refrigerators were logged at one-minute intervals. Personnel from practices with cold chain breaches was offered the eLearning. The primary outcome was the intervention's effectiveness to achieve temperatures in the target range (2 to 8°C) in the sixth week (follow-up) compared to the first (baseline). Using continuous temperature data, a generalized additive model for location, scale and shape was estimated.

Results: The practice response rate was 38% (64 of 168). At baseline, 73% of the practices and 68% of the refrigerators (51 of 75) showed cold chain breaches. 47% of the practices (n = 22 with 24 refrigerators) participated in the eLearning (55 physicians and practice assistants). At follow-up, 17% of those refrigerators were in the target range continuously, 38% reached targets 95% of the time while always >0°C, and temperatures ≤0°C decreased by 63%. Based on 2 million temperature data, the average Euclidian distance based on regression showed a significant improvement (p<0.05).

Conclusion: The eLearning KeepCoool improved the practices´ vaccine cold chain. It is freely available at https://keepcoool.ukbonn.de.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Consort flow-chart with overview on recruitment and follow-up (practices and refrigerators): Stratification by cold chain-breaches and eLearning participation (participants vs. nonparticipants) and monitoring only practices; practice drop-outs: 1 in participants, 2 in nonparticipants, 6 in monitoring.
Fig 2
Fig 2. Timepoint of participation in eLearning stratified by practices (N = 22) and profession for the total temperature monitoring period (>3 months).
Fig 3
Fig 3. Refrigerator temperatures before and after eLearning: Average Euclidean distance of the 95% prediction intervals.
See this image and copyright information in PMC

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